Universal constituency treebanking and parsing: A pilot study

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AIR8EH96X" target="_blank" >RIV/00216208:11320/26:IR8EH96X - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1016/j.csl.2025.101826" target="_blank" >http://dx.doi.org/10.1016/j.csl.2025.101826</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.csl.2025.101826" target="_blank" >10.1016/j.csl.2025.101826</a>

Result language

angličtina

Original language name

Universal constituency treebanking and parsing: A pilot study

Original language description

Universal language processing is crucial for developing models that work across multiple languages. However, universal constituency parsing has lagged due to the lack of annotated universal constituency (UC) treebanks. To address this, we propose two cost-effective approaches. First, we unify existing annotated language-specific treebanks using phrase label mapping to create UC trees, but this is limited to only a handful of languages. Second, we develop a novel method to convert Universal Dependency (UD) treebanks into UC treebanks using large language models (LLMs) with syntactic knowledge, enabling the construction of UC treebanks for over 150 languages. We adopt the graph-based max margin model as our baseline and introduce a language adapter to fine-tune the universal parser. Our experiments show that the language adapter maintains performance for high-resource languages and improves performance for low-resource languages. We evaluate different scales of multilingual pre-trained models, confirming the effectiveness and robustness of our approach. In summary, we conduct the first pilot study on universal constituency parsing, introducing novel methods for creating and utilizing UC treebanks, thereby advancing treebanking and parsing methodologies.1 © 2025 Elsevier Ltd

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2026

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Computer Speech and Language

ISSN

0885-2308

e-ISSN

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Volume of the periodical

95

Issue of the periodical within the volume

2026

Country of publishing house

US - UNITED STATES

Number of pages

16

Pages from-to

1-16

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-105007423678